Abstract

This manuscript is a contribution on the modeling of H.263 traffic in multipoint videoconference sessions over IP Networks. Our study includes analysis and modeling assessment of extensive data gathered during realistic videoconference sessions between commercial H.263-compliant terminal clients (with different videoconference software packages installed). All terminal clients were communicating through a Multipoint Control Unit (software or hardware MCU) at ‘switched presence’ mode and for comparative purposes the same typical videoconference content (a person speaking, with mild movement and occasional zoom/span) was used. The analysis of the H.263 data at the frame level suggests that the traffic from the different terminals to the MCU can be represented by a stationary stochastic process with an AutoCorrelation Function (ACF) rapidly decaying to zero and a Gamma formed marginal frame-size Probability Distribution Function (PDF). An accurate analysis of the H.263 traffic from all terminals (with the same visual content and different videoconference software used) shows indicative differences in the ACF and PDF of different terminals' traffic and insights that no generic traffic model can be applied for all cases. Aiming at a realistic, reusable and simple H.263 traffic model, conservative enough for queueing analysis and network estimation, this study discusses methods for calculating the appropriate model parameters from the observed traffic data and proposes a new technique for unconventional fitting of the PDF. The presented modeling and queueing results indicate the suitability of the proposed models for H.263 traffic modeling in IP networks.

Keywords: H.263 traffic modeling; Multipoint videoconference; MCU; Queueing

Article Outline

1. Introduction

2. Description of the videoconference experiments

3. Analysis of the video data sequences

3.1. Autocorrelation function analysis

3.2. Probability distribution function analysis

3.2.1. PDF analysis of terminal JoinPhone lite

3.2.2. PDF analysis of terminal NetMeeting

3.2.3. PDF analysis of terminal video link pro

3.2.4. PDF analysis of terminal CuSeeMe Pro

3.3. Queueing analysis via the C-DAR(1) model and the fluid-flow method

4. Conclusions

Acknowledgements

References